Export Performance and Innovation Activities in the Agrifood

17 Pages·2002·0.41 MB·English

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Export Performance and Innovation Activities in the
Agrifood Industry: A Recursive Estimation Approach

Mehrez Ameur

Azucena Gracia
e-mail: [email protected]

Paper prepared for presentation at the Xth EAAE Congress
‘Exploring Diversity in the European Agri-Food System’,
Zaragoza (Spain), 28-31 August 2002

Copyright 2002 by Merez Ameur and Azucena Gracia. All rights reserved. Readers may
make verbatim copies of this document for non-commercial purposes by any means,

provided that this copyright notice appears on all such copies.
EXPORT PERFORMANCE AND INNOVATION ACTIVITIES IN THE AGRIFOOD
INDUSTRY: A RECURSIVE ESTIMATION APPROACH

Mehrez AMEUR
Azucena GRACIA
Unidad de Economía Agraria
Servicio de Investigación Agroalimentaria (DGA)
Apdo 727, 50080 Zaragoza (Spain)
Phone: [phone]
Fax: [phone]
e-mail: [email protected]

Summary

Agrifood firms operate in a more global, saturated and competitive market than
other manufacturing firms, and they have smaller size. These firms certainly need to
define appropriate strategies related to accessing the international market and to
investing in innovative activities. This two decisions are related to firms size because as
Krugman states international trade is not only explained by differences in technology
between countries but also by firms’ desire to extend their sales in foreign markets to
take advantage of the economies of scales. Therefore, it seems to exist a simultaneous
relation between firm size, exports and innovative activities.

The aim of this paper is to analyse agrifood firms’ decisions on these three
strategies: export behaviour, innovative activities and firm’s size in comparison to other
manufacturing firms using some modification from the simultaneous model defined by
Entorf and Pohlmeier. The study is focused on the Spanish manufactured firms taking
special attention to the agri-food ones. Data come from a National Survey (“Encuesta de
Estrategias Empresariales”) carried out by the “Fundación Empresa Pública”) from
1990.

Results indicate that agri-food manufacturing firms decision process related to
their size, export share and innovative activities is not a simultaneous process.
Moreover, some differences with the rest of manufactured firms have been detected, In
particular, agri-food firms have lower export shares, lower size and lower innovation
intensity than Spanish firms in other manufacturing sectors. Spanish firms decision
process on strategic variables (size, export share and innovation) is characterized by a
recursive decision process where firms firstly decide export intensity, secondly, they
decide their size or total sales depending on the previous decision and, finally, they
decide their innovative intensity depending on the last two.

1
EXPORT PERFORMANCE AND INNOVATION ACTIVITIES IN THE AGRIFOOD
INDUSTRY: A RECURSIVE ESTIMATION APPROACH

1. Introduction

The economic environment that firms are facing is characterised by two
important phenomena that produce significant changes in all economic activities. One of
them is the globalisation process that induces an increasing in international
competitiveness and in business internationalisation. Firms operating in this competitive
market must undertake international strategies such as exports activities in order to
survive in the market. The second phenomenon is the continuous and important
development in technology that provides firms the opportunity to carry out innovative
activities to differentiate their products in the market. Moreover, agrifood firms face to a
more saturated market than firms operating in other sectors because, food demand is
stagnated in quantities terms although some increases in expenditures can be expected
due to consumers’ claims for higher quality products. Consumers are demanding more
processed, diverse and added-value food products, therefore, agrifood must satisfy these
new requirements and product innovation becomes the means to accomplish these
requirements.

Agrifood industry in Europe is characterised by the small size of the companies
where more than 80% of food manufacturing enterprises employ less than 10 workers,
and only 0.3% employ more than 500 (Traill, 1998). Therefore, most of food companies
are Small and Medium Enterprises (SME) (less than 250 employees according to the
European Commission definition), but largest firms employ 29% of the workers.
Moreover, there are structural differences between countries. The United Kingdom,
Denmark and Sweden have high-concentration industry, Germany and France have
medium levels of concentration, and Italy, Portugal, Belgium, Greece and Ireland have
low levels (Traill, 1997). In the case of Spain, agri-food industry is the first
manufacturing sector and it accounts for 20% of total manufacturing output, employs
15% of total manufacturing workers and represents 16% of total manufacturing
companies in 1999. However, food industry size is relatively small with almost 90% of
food companies with less than 20 workers with in average 14 workers per company
(Ameur, 2002).

Many authors have stated that a large firms size is essential either to undertake
export or innovation activities. In the later, according to Schumpeter, larger firms can
provide the required economies of scale to carry out innovation activities. In the former,
many studies have tried to analyse the positive relationship between firms size and
export performance (Bilkey (1979); Reid (1982); Cavusgil et al. (1979); Bonarcosi
(1992)). They stated that this positive relationship is due to the economies of scale
generated by larger firms and because these larger firms are in a better position to
undertake the higher cost and risk associated to the export activity. On the other hand,
some empirical works have tried to demonstrate the relationship between innovation
and exports. The basic foundation of this relation comes from the pioneers explanations
of international trade where trade is explained by differences in specialisation across
countries. However, recent literature has also argued that actual international trade can
be explained by differences in technology (neotechnology theories). Finally, Krugman
analysed the factors affecting international trade using new assumptions taken from the
2
industrial economics theory (monopolistic competition, economies of scale and product
differentiation). He stated that international trade is not only explained by differences in
technology between countries but also by firms’ desire to extend their sales in foreign
markets to take advantage of the economies of scales. Therefore, it seems to exist a
simultaneous relation between firm size, exports and innovative activities.

This simultaneous relationship was analysed in the eighties by some authors,
Encaoua y Jacquemin (1980), Clarke y Davies (1982) and Neumann et al. (1985),
assuming that firms operate in an imperfect competitive market. Those models were
extended by Entorf and Pohlmeier (1990) and applied in the Spanish manufacturing
sector by Orti and Miravete (1992), Labeaga and Martinez (1993) and Escribano (1995).

Agrifood firms operate in a more global, saturated and competitive market than
other manufacturing firms and they have smaller size, therefore, they will certainly need
to define appropriate strategies related to accessing the international market and to
investing in innovative activities. In this case, to analyse the relationships between firm
size, exports and innovative activities is of crucial importance. The aim of this paper is
to analyse agrifood firms’ decisions on these three strategies: export behaviour,
innovative activities and firm’s size in comparison to other manufacturing firms using
some modification from the simultaneous model defined by Entorf and Pohlmeier. The
study is focused on the Spanish manufactured firms taking special attention to the agri-
food ones. Data come from a National Survey (“Encuesta de Estrategias
Empresariales”) carried out by the “Fundación Empresa Pública”) from 1990.

The paper is structured as follows. Next section defines the theoretical model
used to explain the relationship between exports, innovation and firm size. Section three
describes data and the definition of the variables included in the model. Section four
presents main econometric results and explains the econometric procedure. Finally,
some concluding remarks are presented.

2. The model

The theoretical model used in this paper is a straightforward extension of a
competitive fringe model frequently used in the literature (Encaoua and Jacquemin,
1980, Clark and Davies, 1982; Neuman et al., 1985) and extended by Entorf y
Pohlmeier (1990).

Those authors assumed the same market structure where two different types of
firms are operating. The first group consist of firms behaving as dominant in an
oligopolistic market, and the second group as a competitive fringe. Each firm can sell its
products in the domestic market and in the foreign market assuming that they are
independent. On the other hand, firms decide the total output, how much to sell in each
market and the investment on product innovative activity.

In this paper, it is supposed that firm’s sales can be expanded depending on the
level of the innovation activity, and the increase in sales due to the innovative activity is
considered the same in both markets. In other words, total sales will increase depending
of how much firms spent on product innovative activity.
3
On the domestic market, total demand will be served by “n” dominant firms and
a competitive fringe (consisting of “m” perfectly competitive firms) that can be
expressed as follow:
n
Qd = ∑(1+s(AI ))qd + Xd
j ij ij j
i=1
the demand in the foreign market is modelled equivalently by:
m
Qe = ∑(1+s(AI ))qe + Xe
j ij ij j
i=1
where:
(1+s(AI ))qd: is the output of the dominant i firm of industry j sold in the domestic
j ij
market
(1+s(AI ))qe: is the output of the dominant i firm of industry j sold in the foreign
ij ij
market
Xd : is the total output sold by the competitive fringe in the domestic market
j
Xe: is the total output sold by the competitive fringe in the foreign market
j
s(AI ): is a function expressing the increase in firm total sales due to the innovative
ij
activity.

The total output of the firm “i” in industry “j” sold in both markets is:
(1+s(AI ))q =(1+s(AI ))qd +(1+s(AI ))qe
ij ij ij ij ij ij

Profits of the ith dominant firm in industry j are defined by:

Π =Rd(Qd,qd,AI )+Re(Qe,qe,AI )−costs
ij ij j ij ij ij j ij ij

where, Rd() and Re() are revenues obtained on the domestic and foreign
ij ij
markets, respectively.

Three different types of costs can be defined as:
[ ]
• Production cost: given by CP ((1+s(AI )q ,w ) , where AI is the
ij ij ij ij ij
innovative activity, w is the wage of the workers considered as the only
ij
input that varies in the short-run.
• Innovative cost: given by CI (AI )
ij ij
[ ]
• Export activities cost: given by CE ((1+s(AI )qe,Exe), that depends on
ij ij ij i
the output sold abroad and on other factors related to export difficulties
(market investigation, distance, etc.).

In this short-run model, decisions taken by firms are: Total sales, Export share
and Innovative activity. Therefore, the endogenous variables in the model are: total
qe
sales (q ), export share (λ = ij ) and product innovative activity (AI ).
ij ij q ij
ij

4
To simplify the model we assume that revenues are additively separable in both
markets. Then firm’s decision problem is:

[ ] [ ] [ ]
Π = Pd(Qd)× (1+s(AI )qd +Pe(Qe)× (1+s(AI )qe −CP ((1+s(AI )q ,w )
ij j j ij ij j j ij ij ij ij ij ij
[ ]
−CI (AI )−CE ((1+s(AI )qe,Exe)
ij ij ij ij ij i

where: Pd(Qd) and Pe(Qe) are the inverse demand in the domestic market and the
j j j j
inverse demand in the foreign market, respectively, that depend on the total quantity
sold in each market.

To find the optimum, each dominant firm must maximize its profit function with
respect to the three decision variables. Therefore, the three first order conditions are as
follows:

With respect to the first variable:
[ ] [ ] dCP (q ,w ) dCE(qe,Exe)
(fdqd +Pd)(1−λ )+ (feqe +Pe)(λ )− ij ij ij − ij ij =0
ij j ij ij j ij
dq dq
ij ij
With respect to the second variable:
 dPd(Qd) dPe(Qe)  dCE
[1+s(AI )]×(Pe −Pd)q + j j (1−λ )q + j j λq − ij =0
j  j j ij dλij ij ij dλij ij ij dλij
With respect to the third variable:
Pdqd ds(AIij) +Peqe ds(AIij) + dPjd [1+s(AI )]qd + dPje [1+s(AI )]qe − dCosts =0
j ij dAI j ij dAI dAI ij ij dAI ij ij dAI
ij ij ij ij ij

Once all the derivatives above are rearranged and after inserting each function in
its corresponding equations, a system of equations defining the firm’s optimal choice in
term of these three decision variables, its exogenous firm-specific parameters and the
variables defined at the industry level is obtained (see Ameur (2002) for the explanation
of the derivations). The three equations that define firm’s decisions on firm size, export
share and innovation are the following:

( )
F =F q ,λ,w ,AI ,Qd,ϖd,µd,νd,εd,Kd,Qe,νe,εe,Ke =0
1 1 ij ij ij j j ij ij j j j j j j j
( )
F =F q ,λ,AI Qd,ϖdµd,νd,εd,Kd,Qe,νe,εe,Ke,Exe =0
2 2 ij ij ij, j ij ij ij j j j ij j j ij
( )
F =F q ,λ,AI ,εd,ηd,τd,εe,ηe,τe =0
3 3 ij ij ij j j j ij j ij

The definition of the variables is shown in table 1.

The system can be modelled econometrically as a three simultaneous equation
system in the choice parameters treating all other variables as exogenous. Furthermore,
the system gives some insight on how variables defined at industry level can be
modelled within an econometric model based on firm level data.

5
3. The data

Data come from a continuous survey “Business Strategy Survey” (Encuesta de
Estrategias Empresariales) carried out to manufacture firms by the “Fundación Empresa
Pública” since 1990. The survey collect every year information on the number of
employees by categories, sales and expenditures by type of products, exports and
imports, market share, foreign investment, price policy, market characteristics and
expectative, and accounting information. However, not all variables are gathered every
year, some specific variables are questioned only every four years (Innovation activities,
foreign investment, expected prices, system of production, marketing strategies
(promotion, advertisement), distribution channels, competitors’ strategies perception).
This is the reason why information for the last 5 years (1994-1998) has been used,
because the first and the last year contain information for all the variables.

The survey is conducted to approximately 1400 manufacture firms that are
interviewed yearly. They try to maintain the same set of firms in the database, and if
some firms disappear from the original database, a new firm with similar characteristics
is introduced. Then, to have a homogenous database for the period (1994-1998) we have
deleted some of them and we have finally considered 1358 firms every year. Therefore,
total sample consists of a pool of 1358 firms in 5 years, it means a total of 6790
manufactured firms.

Firms are classified by main-product type in 21 groups according to the
Economic Activities Classification at the three-digit industry level (Ministerio de
Industria y Energia, 1999) (three of the groups correspond to agri-food firms). Survey
information has been used to calculate the variables in the way they have to be included
in the model. Variables definition and calculations can be shown in table 1.

4. Estimation and results

The model to be estimated consists of three equations with three dependent
qe
variables: total sales (q ), export share (λ = ij ) and product innovative activity
ij ij q
ij
(AI ). Two of these variables are truncated to zero λ and AI because firms can be or
ij ij ij
not exporters, and can or not spend on innovation. Moreover, we have to estimate a
simultaneous equations system with truncated variables. This type of econometric
model cannot be estimated with classic simultaneous estimation methods. The most
efficient method to estimate jointly the three equations system would be the maximising
of the likelihood function. However, the likelihood function cannot be defined for
models with more than two equations. Therefore, some authors have used different two-
stage estimation procedures such as Nelson and Olson (1978), Amemiya (1974) to
estimate these simultaneous equation models with truncated variables (Entorf and
Pohlmeier (1990); Orti and Miravete (1992), Labeaga and Martinez (1993) and
Escribano (1995)).

The simultaneous model defined by equation (1)-(2) and (3) has been estimated
using the Nelson and Olson procedure and results are shown in table 2. This estimation
determines that some of the endogenous variables in the model are not statistically
significant explaining the behaviour of the other endogenous variables. In particular, in
6
the export share equation, neither firm size nor innovation activity has statistically
significant effect on export share. The null effect of firm size on export share indicates
that Krugman hypothesis, who states that firms export behaviour is not only due to
differences in specialisation but also because firms try to take advantage of the
economies of scale due to their larger size, is not accepted. Therefore, for the Spanish
manufactures the size is not a factor that encourages their export intensity. On the other
hand, the null effect of the innovation activity on export share is against the a priori
expected hypothesis that the higher product differentiation due to the higher innovation
intensity will increase firm competitive position in the foreign market and, hence, their
export share. Therefore, export decision depends only on the exogenous variables. In
the sales equation, export share has a statistically significant impact on firm size, but the
innovation activity seems not to influence the size of the company. Finally, in the
innovation equation, both, firm size and export share have shown statistically significant
effects on the innovative activity.

Previous results indicate that there are not simultaneous relationships among
variables, although some bilateral relations have been found. Then, Spanish firms do not
take decisions related to their size, export share, and innovation activities
simultaneously. Some variables seem to be related with other variables, but it has not
been detected significant relationships among all the endogenous variables. The final
relationships found in estimations indicate that firms decide firstly their export share
depending on other explicative factors. Secondly, they decide their total sales depending
on the previous decision (export share) and other exogenous variables, and finally firms
will decide their level of innovation depending on both previous decisions along with
some exogenous factors.

This preliminary estimation provides the empirical evidence to allow us to re-
define the original simultaneous system model, following the new structure, as a
recursive equation system. This system consists of three equations: i) export share
depending only on exogenous variables; ii) total sales (firm size) that depend not only
on the exogenous variables but also, on the export share; and iii) innovation activity that
depends on both, export share and firm size, along with a set of exogenous variables.

The recursive equation system can be expressed as follow:

λ*=βExxEx +uEx
i i i
S =βSxS +γSλ* +uS
i i i i
AI * = βAIxAI +γAIλ * +γAIS + uAI
i i 1 i 2 i i

where first and the second variables are truncated to zero and can be expressed as
follow:
λ* =λ ifλ >0
 i i i
λ*i =0 if λi ≤0

AI* = AI if AI >0
 i i i
AIi* =0 if AIi ≤0

7
This new system of equations will be estimated by maximizing likelihood
function.
The likelihood function for the three recursive equation system to be maximized is1:
( ) −βEXxEX 
LβEX, βS,γS,βAI,γAI,γAI = ∑ lnΦ i  +
1 2  σ 
λi≤0  E 
∑ lnΦ−βAI×iAI −γ1AI ×λi −γ2AI ×Si +Σ21Σ1−11U1−ln(2π)− 1ln(Σ )− 1Z' Σ−1U 
λi≥0   σI.ES  2 11 2 1 11 1
AI≤0
i
− ∑ 1 {3 ln(2π) + ln(Σ)+ U' Σ−1 U }
2 2 2
λ>0
i
AI >0
i

To estimate this recursive model, the above likelihood function for the system of
equations will be maximized to obtain the maximum likelihood estimated parameters
for all the variables introduced in the model. Results of this estimation are shown in
table 3.

Estimated parameters in the export share equation show that all the coefficients
are statistically significant except for three of them: total sales sold in the domestic, total
sales sold in the foreign market, and the number of products manufactured by the firm.
The market share in the domestic market has a negative sign and statistically different
from zero which means that market share has a negative effect on export share while the
market share in the foreign market has a positive and statistically different from zero
effect. Those results indicate that firms with higher shares in the domestic market have
less incentive to sell their products in the foreign market because their relatively
importance in the domestic market is high enough, while firms with higher shares in the
foreign market reach higher export share. It means that the larger their market share in
the foreign market is the larger firms’ export share is. So that, for the Spanish firms it is
difficult to start exporting mainly for those firms with high participation in the domestic
market, but once they have accessed to the international market, they allocate increasing
proportion of their sales in this market.

The effect of the total demand price elasticity on the export share is positive and
statistically different from zero. This indicates that positive expectations on the
domestic market grown (higher elasticity) will stimulate firms to export higher
proportion of their total output. Concentration ratio has also a positive effect on the
export share, which indicates that firms operating in highly concentrated domestic
market will search for alternative markets, less concentrated, to reach a certain level of
sales and, therefore, they will have higher export share. The number of intermediaries in
the distribution chain has a negative effect on the export share. In other words, if the
retailers chain consist of a higher number of intermediaries, it is less likely that firms
have higher exports. Finally, the closer country destination of exports is the highest firm
export shares are. This is due mainly to three reasons, neighbours have more similar
tastes, the access to information about foreign market structures is higher and
transportation costs are lower.

In the firm size (total sales) equation, export share has a significant negative
effect. This effect can be explained by the lower firms incentive to sell abroad of larger

1 See explanations in the annex
8